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During the second half of the twentieth century pollution became a relevant problem, but after the seventies many governments began legislating against emissions. From then on, air pollution decreased as new technologies replaced older ones and now transportation, both private and public, is no longer the main source of pollution in modern countries (it still is in third world areas). Today urban trafficper se is the main problem. The pollution traffic component being relegated in the background, many governments and local administrations address the "congestion factor" by introducing regulations to reduce private traffic, considered the main source of congestion: access tolls and (public transport/car pools) dedicated lanes and odd measures such as narrowing lanes (and/or reducing their number), lowering speed limits, reducing parking availability, etc. Geolocation and road navigation technologies, combined with widespread mobile connectivity infrastructures have enabled researchers to study the evolution of traffic at a great depth. To the extent that some vendor, namely TomTom, uses collected customer navigators' data to publish annual reports - the "TomTom Traffic Index" - about the state of congestion in major cities around the world. One proposed solution to congestion or, better, to the underusage of private vehicles, is the so called "carsharing", i.e., pools of vehicles to be rented for short periods of time (minutes, hours), usually at higher costs (per day) than standard car rental prices. In many urban areas, such as Milan, where the authors live, measures against congestion are combinedly applied, e.g., tolls to enter a particular area, carsharing (with access to the paying area included), dedicated lanes, ban for certain types (older ones) of vehicles. Carsharing vendors "publish" (not entirely/easily accessible) data about the state of their vehicle pool. Can this data be used to analyze these services' effect, efficiency, usefulness, social cost, etc.? The authors scraped carsharing vendors' websites for a year, made this huge amount of data uniform, fed it into a mongodb database and then "played" with queries and graphed results. An interesting finding is that even on the carsharing pool a "lung effect" (people moving-in in the morning, moving-out in the evening) is evident, i.e., the common notion that carsharing is not for commuters can be argued. Another interesting behaviour is the evening peak usage, i.e., probably, caused by people using carsharing instead of taxicabs to go out at night (leisure). Moreover, the data show that vehicle usage (the total number of "busy" vehicles at any time) never goes beyond 70%, i.e., there is always a 30% pool of "free" vehicles. Throughout the paper interesting statistical data and graphs will be shown and discussed.

Vehicle detection from satellite imagery can support different applications, such as security and situational awareness. In the civilian domain, it can provide quantitative evidence to investigate urban mobility and traffic patterns in cities. Satellite synthetic aperture radar (SAR) can help in detecting vehicles in (almost) all weather conditions and during the day and night. In this study, the capability of SAR StripMap imaging mode data to monitor traffic is analyzed using the case study of Wuhan, China. In ordinary times, the bridges crossing the Yangtze river are the key infrastructure allowing for urban mobility in Wuhan. More recently, the city has been the first in the world to be put in lockdown due to the outbreak of the Coronavirus Disease of 2019 (COVID-19). Using a very long time series of 294 COSMO-SkyMed StripMap HIMAGE mode scenes collected from 2011 to 2020, we detected vehicles on seven bridges, estimated their speed, and analyzed the traffic pattern over time. Vehicles are detected based on their azimuth shift caused by their across-track motion. Our goal is to monitor the variations in traffic instead of single-car detection. The results from 2011 to 2019 show a general increase in the number of vehicles crossing the bridges, as new infrastructure was built over the years. Variations in detected vehicle numbers were especially found during the two events of the 7th International Military Sports Council (CISM) Military World Games in October 2019, and the COVID-19 lockdown in early 2020. These events were therefore used for internal validation of our assessment of traffic patterns. On the other side, TomTom traffic index data were used for external validation. The results and their comparison with TomTom data prove the effectiveness of our method in detecting traffic patterns, but also demonstrate that mostly large vehicles (e.g., trucks or buses) are detected. Future work should be carried out to improve the detection rate of smaller vehicles.

The objective of this study is to characterize the nature and space-time patterns of traffic accidents involving elderly pedestrians in Sweden, in order to suggest preventive measures. The analysis is based on elderly pedestrian accidents from 2010 to 2014 using an age adjusted standardized elderly accidents ratios (ASEAR), Geographical Information Systems (GIS) and spatial statistics techniques. Findings show that the geography of elderly traffic accidents is far from being homogenous across the country: although most accidents happen in urban municipalities, 30 per cent of municipalities classified as accessible rural exhibit relatively high-standardized accidents ratios. They happen often in daylight hours, on weekdays and in the coldest months of the year. Most of the cases are single accidents (e.g. self-inflicted fall); they happen in street segments/intersections and pedestrian/bicycle path, some affected by environment conditions such as icy or uneven surfaces. Findings of the study call for preventive actions that are sensitive to the nature of these accidents in different temporal and spatial contexts.

The traffic flow pattern of the material distribution activity
within the Canadian Forces was evaluated. The aim was to validate the
current operation of the material traffic system. Sample transportation
data were collected, and the traffic flow pattern and utilisations of
the Canadian Forces′ scheduled tractor‐trailer units were statistically
inferred. Because historical material traffic data were lacking, the
material traffic flow pattern for this one‐time snapshot of the
transportation system did not provide a basis from which any trend on
the Canadian Forces′ vehicle utilisation could be established.

Traffic measurements in broadband access networks are crucial from several points of view. A better understanding of traffic patterns can lead to more efficient network design, which leads to energy and cost savings for the operator and improved end user services. This paper reports on selected traffic measurement results from the Celtic TRAMMS project. The measurements were performed in broadband access networks in Sweden and Spain. The vast majority of the traffic volume is video based and from peer-to-peer applications. This suggests that future access networks should be symmetrical in order to properly cope with the traffic patterns of the future. Geographic locality of end-to-end flows has been identified for incoming and outgoing traffic in Spain, which may be used to analyze peering between ISP's. Finally, we show that stricter legislation in Sweden targeting illegal file sharing led to a dramatic decrease of the traffic. This means that factors not controlled by the networking community may seriously impact traffic patterns and user behaviour thereby indicating the need for closer collaboration between researchers and network designers on one side and politicians and regulators on the other side.

Despite extensive efforts to understand the overall effect of urban structure on the current patterns of urban mobility, we are still quite far away from a consensual perspective on this complex matter.